{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true,
    "pycharm": {
     "is_executing": true
    }
   },
   "source": [
    "# AIOps anomaly detection"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Anomaly detection detects data points in data that does not fit well with the rest of data. In this notebook we demonstrate how to do anomaly detection using Zouwu's built-in model MTNet"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "For demonstration, we use the publicly available cluster trace data cluster-trace-v2018 of Alibaba Open Cluster Trace Program. You can find the dataset introduction <a href=\"https://github.com/alibaba/clusterdata/blob/master/cluster-trace-v2018/trace_2018.md\" target=\"_blank\">here</a>. In particular, we use machine usage data to demonstrate anomaly detection, you can download the separate data file directly with <a href=\"http://clusterdata2018pubcn.oss-cn-beijing.aliyuncs.com/machine_usage.tar.gz\" target=\"_blank\">machine_usage</a>."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Helper functions"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This section defines some helper functions to be used in the following procedures. You can refer to it later when they're used."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "def get_drop_ts_and_len(df, target_col=\"cpu_usage\", allow_missing_num=3):\n",
    "    \"\"\"\n",
    "    get start index which with consecutive missing num larger than allow_missing_num\n",
    "    \"\"\"\n",
    "    missing_num = df[target_col].isnull().astype(int).groupby(df[target_col].notnull().astype(int).cumsum()).sum()\n",
    "    missing_num = missing_num[missing_num > 0]\n",
    "    drop_ts = df.iloc[(missing_num.index + missing_num.cumsum() - missing_num).values].index\n",
    "    drop_ts = drop_ts[missing_num > allow_missing_num]\n",
    "    drop_missing_num = missing_num[missing_num > allow_missing_num]\n",
    "    drop_len = drop_missing_num.values\n",
    "    return drop_ts, drop_len"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "def rm_missing_day(start_dts, missing_lens, df):\n",
    "    \"\"\"\n",
    "    drop days with consecutive missing values.\n",
    "    If consecutive missing values across day, we remove the data for an extra hour.\n",
    "    \"\"\" \n",
    "    for start_time, l in zip(start_dts, missing_lens):\n",
    "        start = start_time.replace(hour=0, minute=0, second=0)\n",
    "        start_day_end = start + pd.Timedelta(hours=24)\n",
    "        start_day_end = start_day_end - pd.Timedelta(minutes=1)\n",
    "        end_time = start_time + l*pd.Timedelta(minutes=1)\n",
    "        if start_day_end < end_time:\n",
    "            end = end_time + pd.Timedelta(hours=1)\n",
    "        else:\n",
    "            end = start_day_end\n",
    "        df = df.drop(df[start:end].index)\n",
    "    return df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "def train_val_test_split(df, val_ratio, test_ratio, look_back, horizon):\n",
    "    \"\"\"\n",
    "    Split the dataset into train, validation and test part.\n",
    "    \"\"\" \n",
    "    total_num = df.index.size\n",
    "    test_num = int(total_num * test_ratio)\n",
    "    val_num = int(total_num * val_ratio)\n",
    "    \n",
    "    test_split_index = test_num + look_back + horizon - 1\n",
    "    val_split_index = test_split_index + val_num \n",
    "    \n",
    "    train_df = df.iloc[:-(test_num + val_num)]  \n",
    "    val_df = df.iloc[-val_split_index: -test_num]\n",
    "    test_df = df.iloc[-test_split_index: ]\n",
    "    \n",
    "    return train_df, val_df, test_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "def roll_data(dataset, look_back, target_col_index):\n",
    "    \"\"\"\n",
    "    Generate input samples from rolling\n",
    "    \"\"\"\n",
    "    X, Y = [], []\n",
    "    for i in range(len(dataset) - look_back):\n",
    "        X.append(dataset[i: (i + look_back)])\n",
    "        Y.append(dataset[i + look_back, [target_col_index]])\n",
    "    return np.array(X), np.array(Y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "def unscale(scaler, y, target_col_indexes):\n",
    "    \"\"\"\n",
    "    data needs to be normalized (scaled) before feeding into models. \n",
    "    This is to inverse the effect of normalization to get reasonable forecast results.\n",
    "    \"\"\"\n",
    "    dummy_feature_shape = scaler.scale_.shape[0]\n",
    "    y_dummy = np.zeros((y.shape[0], dummy_feature_shape))\n",
    "    y_dummy[:, target_col_indexes] = y\n",
    "    y_unscale = scaler.inverse_transform(y_dummy)[:,target_col_indexes]\n",
    "    return y_unscale"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "EPSILON = 1e-10\n",
    "def sMAPE(y_true, y_pred):\n",
    "    \"\"\"\n",
    "    Symmetric Mean Average Percentage Error\n",
    "    \"\"\"\n",
    "    output_errors = np.mean(100 * np.abs(y_true - y_pred)/(np.abs(y_true) + np.abs(y_pred) + EPSILON), axis=0,)\n",
    "    return np.mean(output_errors)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_result_df(df, y_pred_unscale, ano_index, look_back,target_col='cpu_usage'):\n",
    "    \"\"\"\n",
    "    Add prediction and anomaly value to dataframe.\n",
    "    \"\"\"\n",
    "    result_df = pd.DataFrame({\"y_true\":df[look_back:][target_col], \"y_pred\": y_pred_unscale.squeeze()})\n",
    "    result_df['anomalies'] = 0\n",
    "    result_df.loc[result_df.index[ano_index], 'anomalies'] = 1\n",
    "    result_df['anomalies'] = result_df['anomalies'] > 0\n",
    "    return result_df "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "def plot_anomalies_value(date, y_true, y_pred, anomalies):\n",
    "    \"\"\"\n",
    "    plot the anomalies value\n",
    "    \"\"\"\n",
    "    fig, axs = plt.subplots(figsize=(16,6))\n",
    "    \n",
    "    axs.plot(date, y_true,color='blue', label='y_true')\n",
    "    axs.plot(date, y_pred,color='orange', label='y_pred')\n",
    "    axs.scatter(date[anomalies].tolist(), y_true[anomalies], color='red', label='anomalies value')\n",
    "    axs.set_title('the anomalies value')\n",
    "    \n",
    "    plt.xlabel('datetime')\n",
    "    plt.legend(loc='upper left')\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "## Download raw dataset and load into dataframe"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "Now we download the dataset and load it into a pandas dataframe.Steps are as below:\n",
    "* First, download the raw data <a href=\"http://clusterdata2018pubcn.oss-cn-beijing.aliyuncs.com/machine_usage.tar.gz\" target=\"_blank\">machine_usage</a>. Or run the script `get_data.sh` to download the raw data.It will download the resource usage of each machine from m_1932 to m_2085. \n",
    "* Second, run `grep m_1932 machine_usage.csv > m_1932.csv` to extract records of machine 1932. Or run `extract_data.sh`.We use machine 1932 as an example in this notebook.You can choose any machines in the similar way.\n",
    "* Finally, use pandas to load `m_1932.csv` into a dataframe as shown below."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "import os \n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "df_1932 = pd.read_csv(\"m_1932.csv\", header=None, usecols=[1,2,3], names=[\"time_step\", \"cpu_usage\",\"mem_usage\"])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "Below are some example records of the data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>time_step</th>\n",
       "      <th>cpu_usage</th>\n",
       "      <th>mem_usage</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>386640</td>\n",
       "      <td>41</td>\n",
       "      <td>92</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>386670</td>\n",
       "      <td>43</td>\n",
       "      <td>92</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>386690</td>\n",
       "      <td>44</td>\n",
       "      <td>92</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>386800</td>\n",
       "      <td>46</td>\n",
       "      <td>92</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>386930</td>\n",
       "      <td>44</td>\n",
       "      <td>93</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   time_step  cpu_usage  mem_usage\n",
       "0     386640         41         92\n",
       "1     386670         43         92\n",
       "2     386690         44         92\n",
       "3     386800         46         92\n",
       "4     386930         44         93"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_1932.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x10e7eaf98>"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df_1932.sort_values(by=\"time_step\").plot(y=\"cpu_usage\", x=\"time_step\", figsize=(16,6),title=\"cpu_usage of machine 1932\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "## Data pre-processing"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "Now we need to do data cleaning and preprocessing on the raw data. Note that this part could vary for different dataset. \n",
    "\n",
    "For the machine_usage data, the pre-processing contains 2 parts:\n",
    "1. Change the time unit from seconds to minutes, which is calculated by averaging `cpu_usage` within the minutes.\n",
    "2. Check missing values and handle missing data(fill or drop)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Change the time unit to minute."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "df_1932[\"ts_min\"] = df_1932[\"time_step\"]//60"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Calculate the average of cpu_usage in the same time and draw the line chart."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "resampled_df = df_1932.groupby(\"ts_min\").agg({\"cpu_usage\":\"mean\"})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1038c5780>"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "resampled_df.plot(figsize=(16,6),title=\"mean cpu_usage of machine 1932\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We need datetime information to generate related features,so re-adjust time series."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "resampled_df.index = pd.to_datetime(resampled_df.index, unit='m', origin=pd.Timestamp('2018-01-01'))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Ensure the time interval of dataframe is the same."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "full_idx = pd.date_range(start=resampled_df.index.min(), end=resampled_df.index.max(),freq='T')\n",
    "resampled_df = resampled_df.reindex(full_idx)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>cpu_usage</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2018-01-01 00:56:00</th>\n",
       "      <td>19.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-01-01 00:57:00</th>\n",
       "      <td>19.666667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-01-01 00:58:00</th>\n",
       "      <td>19.666667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-01-01 00:59:00</th>\n",
       "      <td>20.833333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-01-01 01:00:00</th>\n",
       "      <td>25.666667</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                     cpu_usage\n",
       "2018-01-01 00:56:00  19.000000\n",
       "2018-01-01 00:57:00  19.666667\n",
       "2018-01-01 00:58:00  19.666667\n",
       "2018-01-01 00:59:00  20.833333\n",
       "2018-01-01 01:00:00  25.666667"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "resampled_df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "Here, we drop day with more than 3 consecutive missing values and fill other missing values remained."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "drop_ts,drop_len = get_drop_ts_and_len(resampled_df,allow_missing_num=3)\n",
    "df = rm_missing_day(drop_ts, drop_len,resampled_df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>cpu_usage</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2018-01-03 00:00:00</th>\n",
       "      <td>29.666667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-01-03 00:01:00</th>\n",
       "      <td>33.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-01-03 00:02:00</th>\n",
       "      <td>37.833333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-01-03 00:03:00</th>\n",
       "      <td>34.666667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-01-03 00:04:00</th>\n",
       "      <td>37.166667</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                     cpu_usage\n",
       "2018-01-03 00:00:00  29.666667\n",
       "2018-01-03 00:01:00  33.000000\n",
       "2018-01-03 00:02:00  37.833333\n",
       "2018-01-03 00:03:00  34.666667\n",
       "2018-01-03 00:04:00  37.166667"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "no. of n/a values:\n",
      "cpu_usage    21\n",
      "dtype: int64\n"
     ]
    }
   ],
   "source": [
    "print(\"no. of n/a values:\")\n",
    "print(df.isna().sum())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "df.ffill(inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x102ae3128>"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df.plot(figsize=(16,6))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "## Feature Engineering"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "For feature engineering, we use hour as features."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "df[\"hour\"] = df.index.hour"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>cpu_usage</th>\n",
       "      <th>hour</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2018-01-03 00:00:00</th>\n",
       "      <td>29.666667</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-01-03 00:01:00</th>\n",
       "      <td>33.000000</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-01-03 00:02:00</th>\n",
       "      <td>37.833333</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-01-03 00:03:00</th>\n",
       "      <td>34.666667</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-01-03 00:04:00</th>\n",
       "      <td>37.166667</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                     cpu_usage  hour\n",
       "2018-01-03 00:00:00  29.666667     0\n",
       "2018-01-03 00:01:00  33.000000     0\n",
       "2018-01-03 00:02:00  37.833333     0\n",
       "2018-01-03 00:03:00  34.666667     0\n",
       "2018-01-03 00:04:00  37.166667     0"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "## Data preparation"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "Now we split the dataset into train, validation and test."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "val_ratio = 0.1\n",
    "test_ratio = 0.1\n",
    "# we look back one hour data which is of the frequency of 1min.\n",
    "look_back = 60\n",
    "horizon = 1\n",
    "\n",
    "train_df, val_df, test_df = train_val_test_split(df, val_ratio, test_ratio, look_back, horizon)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(6912, 924, 924)"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train_df.index.size, val_df.index.size, test_df.index.size"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "Then standardize train, test data and features"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "from sklearn.preprocessing import StandardScaler\n",
    "standard_scaler = StandardScaler()\n",
    "scaled_train = standard_scaler.fit_transform(train_df)\n",
    "scaled_val = standard_scaler.transform(val_df)\n",
    "scaled_test = standard_scaler.transform(test_df)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "Last, we generate model input samples by sliding window along time axis. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "x_train, y_train = roll_data(scaled_train, look_back, target_col_index=0)\n",
    "x_val, y_val = roll_data(scaled_val, look_back, target_col_index=0)\n",
    "x_test, y_test = roll_data(scaled_test, look_back, target_col_index=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "((864, 60, 2), (864, 1))"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x_test.shape, y_test.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "## Time series forecasting"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "from zoo.zouwu.model.forecast import MTNetForecaster"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "First, we initialize a mtnet_forecaster according to input data shape. Specifcally, look_back should equal `(long_series_num+1)*series_length` . Details refer to zouwu docs <a href=\"https://analytics-zoo.github.io/master/#Zouwu/overview\" target=\"_blank\">here</a>."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "WARNING:tensorflow:From /anaconda3/envs/automl/lib/python3.6/site-packages/tensorflow_core/python/keras/initializers.py:94: calling TruncatedNormal.__init__ (from tensorflow.python.ops.init_ops) with dtype is deprecated and will be removed in a future version.\n",
      "Instructions for updating:\n",
      "Call initializer instance with the dtype argument instead of passing it to the constructor\n",
      "WARNING:tensorflow:From /anaconda3/envs/automl/lib/python3.6/site-packages/tensorflow_core/python/ops/resource_variable_ops.py:1630: calling BaseResourceVariable.__init__ (from tensorflow.python.ops.resource_variable_ops) with constraint is deprecated and will be removed in a future version.\n",
      "Instructions for updating:\n",
      "If using Keras pass *_constraint arguments to layers.\n"
     ]
    }
   ],
   "source": [
    "mtnet_forecaster = MTNetForecaster(target_dim=horizon,\n",
    "                                   feature_dim=x_train.shape[-1],\n",
    "                                   long_series_num=3,\n",
    "                                   series_length=15\n",
    "    )"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "MTNet needs to preprocess the X into another format, so we call `MTNetForecaster.preprocess_input` on train_x and test_x."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "# mtnet requires reshape of input x before feeding into model.\n",
    "x_train_mtnet = mtnet_forecaster.preprocess_input(x_train)\n",
    "x_val_mtnet = mtnet_forecaster.preprocess_input(x_val)\n",
    "x_test_mtnet = mtnet_forecaster.preprocess_input(x_test)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "Now we train the model and wait till it finished."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "WARNING:tensorflow:From /anaconda3/envs/automl/lib/python3.6/site-packages/tensorflow_core/python/ops/math_grad.py:1424: where (from tensorflow.python.ops.array_ops) is deprecated and will be removed in a future version.\n",
      "Instructions for updating:\n",
      "Use tf.where in 2.0, which has the same broadcast rule as np.where\n",
      "Train on 6852 samples\n",
      "Epoch 1/20\n",
      "6852/6852 [==============================] - 25s 4ms/sample - loss: 0.5896 - mean_squared_error: 0.5736\n",
      "Epoch 2/20\n",
      "6852/6852 [==============================] - 17s 2ms/sample - loss: 0.4529 - mean_squared_error: 0.3615\n",
      "Epoch 3/20\n",
      "6852/6852 [==============================] - 15s 2ms/sample - loss: 0.3644 - mean_squared_error: 0.2388\n",
      "Epoch 4/20\n",
      "6852/6852 [==============================] - 15s 2ms/sample - loss: 0.3381 - mean_squared_error: 0.2067\n",
      "Epoch 5/20\n",
      "6852/6852 [==============================] - 16s 2ms/sample - loss: 0.3256 - mean_squared_error: 0.1928\n",
      "Epoch 6/20\n",
      "6852/6852 [==============================] - 15s 2ms/sample - loss: 0.3195 - mean_squared_error: 0.1862\n",
      "Epoch 7/20\n",
      "6852/6852 [==============================] - 15s 2ms/sample - loss: 0.3167 - mean_squared_error: 0.1840\n",
      "Epoch 8/20\n",
      "6852/6852 [==============================] - 15s 2ms/sample - loss: 0.3101 - mean_squared_error: 0.1765\n",
      "Epoch 9/20\n",
      "6852/6852 [==============================] - 15s 2ms/sample - loss: 0.3073 - mean_squared_error: 0.1733\n",
      "Epoch 10/20\n",
      "6852/6852 [==============================] - 14s 2ms/sample - loss: 0.3068 - mean_squared_error: 0.1738\n",
      "Epoch 11/20\n",
      "6852/6852 [==============================] - 15s 2ms/sample - loss: 0.3031 - mean_squared_error: 0.1692\n",
      "Epoch 12/20\n",
      "6852/6852 [==============================] - 14s 2ms/sample - loss: 0.3042 - mean_squared_error: 0.1703\n",
      "Epoch 13/20\n",
      "6852/6852 [==============================] - 15s 2ms/sample - loss: 0.2996 - mean_squared_error: 0.1668\n",
      "Epoch 14/20\n",
      "6852/6852 [==============================] - 15s 2ms/sample - loss: 0.3004 - mean_squared_error: 0.1664\n",
      "Epoch 15/20\n",
      "6852/6852 [==============================] - 14s 2ms/sample - loss: 0.2970 - mean_squared_error: 0.1644\n",
      "Epoch 16/20\n",
      "6852/6852 [==============================] - 14s 2ms/sample - loss: 0.2988 - mean_squared_error: 0.1650\n",
      "Epoch 17/20\n",
      "6852/6852 [==============================] - 14s 2ms/sample - loss: 0.2977 - mean_squared_error: 0.1642\n",
      "Epoch 18/20\n",
      "6852/6852 [==============================] - 15s 2ms/sample - loss: 0.2974 - mean_squared_error: 0.1645\n",
      "Epoch 19/20\n",
      "6852/6852 [==============================] - 15s 2ms/sample - loss: 0.2968 - mean_squared_error: 0.1626\n",
      "Epoch 20/20\n",
      "6852/6852 [==============================] - 14s 2ms/sample - loss: 0.2950 - mean_squared_error: 0.1626\n",
      "CPU times: user 16min, sys: 1min 57s, total: 17min 57s\n",
      "Wall time: 5min 15s\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "hist = mtnet_forecaster.fit(x = x_train_mtnet, y = y_train, batch_size=128, epochs=20)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "Use the model for prediction and inverse the scaling of the prediction results. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "y_pred_val = mtnet_forecaster.predict(x_val_mtnet)\n",
    "y_pred_test = mtnet_forecaster.predict(x_test_mtnet)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "y_pred_val_unscale = unscale(standard_scaler, y_pred_val, [0])\n",
    "y_pred_test_unscale = unscale(standard_scaler, y_pred_test, [0])\n",
    "y_val_unscale = unscale(standard_scaler,y_val,[0])\n",
    "y_test_unscale = unscale(standard_scaler,y_test,[0])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "Calculate the symetric mean absolute percentage error."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "sMAPE is 5.007178919584265\n"
     ]
    }
   ],
   "source": [
    "# evaluate with sMAPE\n",
    "print(\"sMAPE is\",sMAPE(y_pred_test_unscale, y_test_unscale))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "## Anomaly detection"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The threshold of validation dataset is: 14.632055810957759\n"
     ]
    }
   ],
   "source": [
    "from zoo.zouwu.model.anomaly import ThresholdDetector, ThresholdEstimator\n",
    "\n",
    "ratio=0.01\n",
    "threshold = ThresholdEstimator().fit(y=y_val_unscale,yhat=y_pred_val_unscale,ratio=ratio)\n",
    "print(\"The threshold of validation dataset is:\",threshold)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The index of anomalies in validation dataset is: [55, 112, 265, 436, 502, 625, 632, 641, 842]\n",
      "The index of anomalies in test dataset is: [68, 79, 336, 397, 443, 532, 693, 694, 695, 696, 809, 811, 823, 827, 829, 838, 843, 846, 849, 852, 854, 856, 858, 860, 861]\n"
     ]
    }
   ],
   "source": [
    "val_res_ano_idx = ThresholdDetector().detect(y=y_val_unscale,yhat=y_pred_val_unscale,threshold=threshold)\n",
    "test_res_ano_idx = ThresholdDetector().detect(y=y_test_unscale,yhat=y_pred_test_unscale,threshold=threshold)\n",
    "print(\"The index of anomalies in validation dataset is:\",val_res_ano_idx)\n",
    "print(\"The index of anomalies in test dataset is:\",test_res_ano_idx)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "Get a new dataframe which contains `y_true`，`y_pred`，`anomalies` value."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "val_result_df = get_result_df(val_df, y_pred_val_unscale, val_res_ano_idx, look_back)\n",
    "test_result_df = get_result_df(test_df, y_pred_test_unscale, test_res_ano_idx, look_back)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "Draw anomalies in line chart."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_anomalies_value(val_result_df.index, val_result_df.y_true, val_result_df.y_pred, val_result_df.anomalies)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_anomalies_value(test_result_df.index, test_result_df.y_true, test_result_df.y_pred, test_result_df.anomalies)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.10"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 1
}
